Unveiling the Prognostic Potential of Metabolic Genes in Lung Adenocarcinoma

: Lung cancer remains the foremost cause of cancer-related mortality worldwide, with lung adenocarcinoma (LUAD) being its most prevalent subtype. The metabolic reconfiguration within the tumor is vital for the initiation and progression of LUAD. Such metabolic reprogramming includes changes in pathways like glycolysis, lipid metabolism, and oxidative phosphorylation, all of which are critical for the proliferation and survival of tumors. A comprehensive understanding of the molecular dynamics of these metabolic pathways is crucial for refining prognostic assessments and formulating targeted treatments for patients with LUAD. Our research aims to clarify how metabolic gene profiles influence overall survival rates among LUAD patients. By pinpointing significant metabolic genes, we aspire to improve personalized care strategies and enhance clinical outcomes for individuals afflicted by this malignancy. Methods: Gene sets associated with the metabolism were obtained from the Cancer Cell Metabolism Gene Database (ccmGDB). This data supports an in-depth exploration into metabolism-related genes in various cancers. We applied Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) techniques to identify the prognostic genes linked to overall survival. Patients were categorized into high-risk and low-risk groups based on the median value of their risk scores. To evaluate patient outcomes within these categories, Kaplan-Meier survival curves were constructed. The efficacy of the model in differentiating between risk categories was assessed through Receiver Operating Characteristic (ROC) curves. Results: We developed a prognostic model for LUAD based on seven identified metabolic-related genes including GCKR, B۴GALT۱, PIK۳CG, ACSL۳, LDHA, EXT۱, and HSPA۱B. Cox and LASSO regression models were employed to discern these genes. Patients classified as low-risk demonstrated substantially better clinical outcomes than those identified as high-risk. ROC curve analysis validated the model's accuracy in predicting survival at one, two, and three years. Conclusion: This study underscores the critical role of metabolic genes in LUAD outcomes. The prognostic model developed herein, utilizing a panel of metabolic-related genes, offers a valuable tool for precisely predicting patient survival. By delving deeper into the behavior of metabolic-associated genes, we can refine prognostic accuracy in LUAD, enabling more personalized therapeutic approaches.

کلیدواژه ها:

Lung Adenocarcinoma ، metabolic genes ، Prognosis ، Overall Survival